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Almost definitely the only sensible what to achieve this is using random hashing. Other methods such as PCA require a magnitude of overhead similar the task being performed. E.g it will take as long to calculate the eigenvectors as it will to just run the software without PCA. Hense random hashing.
Still need to investigate the best technique.
This will have a dramatic effect of scalability, since the compute time would not be sensitive to number of features any more. Reducing the asymptotic run time of all-pair down to $O(N^2)$ from $O(N^2M)$
The text was updated successfully, but these errors were encountered:
Almost definitely the only sensible what to achieve this is using random hashing. Other methods such as PCA require a magnitude of overhead similar the task being performed. E.g it will take as long to calculate the eigenvectors as it will to just run the software without PCA. Hense random hashing.
Still need to investigate the best technique.
This will have a dramatic effect of scalability, since the compute time would not be sensitive to number of features any more. Reducing the asymptotic run time of all-pair down to$O(N^2)$ from $O(N^2M)$
The text was updated successfully, but these errors were encountered: